def iris2quakeml(url, output_folder=None):
if "/spudservice/" not in url:
url = url.replace("/spud/", "/spudservice/")
if url.endswith("/"):
url += "quakeml"
else:
url += "/quakeml"
print("Downloading %s..." % url)
r = urllib.request.urlopen(url)
if r.code != 200:
r.close()
msg = "Error Downloading file!"
raise Exception(msg)
# For some reason the quakeml file is escaped HTML.
h = html.parser.HTMLParser()
data = h.unescape(r.read().decode('utf-8'))
r.close()
data = StringIO(data)
try:
cat = read_events(data)
except BaseException:
msg = "Could not read downloaded event data"
raise ValueError(msg)
cat.events = cat.events[:1]
ev = cat[0]
# Parse the event and get the preferred focal mechanism. Then get the
# origin and magnitude associated with that focal mechanism. All other
# focal mechanisms, origins and magnitudes will be removed. Just makes it
# simpler and less error prone.
if ev.preferred_focal_mechanism():
ev.focal_mechanisms = [ev.preferred_focal_mechanism()]
else:
ev.focal_mechanisms = [ev.focal_mechanisms[:1]]
# Set the origin and magnitudes of the event.
mt = ev.focal_mechanisms[0].moment_tensor
ev.magnitudes = [mt.moment_magnitude_id.get_referred_object()]
ev.origins = [mt.derived_origin_id.get_referred_object()]
event_name = get_event_filename(ev, "GCMT")
if output_folder:
event_name = os.path.join(output_folder, event_name)
cat.write(event_name, format="quakeml", validate=True)
print("Written file", event_name)
def iris2quakeml(url, output_folder=None):
if "/spudservice/" not in url:
url = url.replace("/spud/", "/spudservice/")
if url.endswith("/"):
url += "quakeml"
else:
url += "/quakeml"
print "Downloading %s..." % url
r = urllib2.urlopen(url)
if r.code != 200:
r.close()
msg = "Error Downloading file!"
raise Exception(msg)
# For some reason the quakeml file is escaped HTML.
h = HTMLParser.HTMLParser()
data = h.unescape(r.read())
r.close()
data = StringIO(data)
try:
cat = readEvents(data)
except:
msg = "Could not read downloaded event data"
raise ValueError(msg)
cat.events = cat.events[:1]
ev = cat[0]
# Parse the event and get the preferred focal mechanism. Then get the
# origin and magnitude associated with that focal mechanism. All other
# focal mechanisms, origins and magnitudes will be removed. Just makes it
# simpler and less error prone.
if ev.preferred_focal_mechanism():
ev.focal_mechanisms = [ev.preferred_focal_mechanism()]
else:
ev.focal_mechanisms = [ev.focal_mechanisms[:1]]
# Set the origin and magnitudes of the event.
mt = ev.focal_mechanisms[0].moment_tensor
ev.magnitudes = [mt.moment_magnitude_id.getReferredObject()]
ev.origins = [mt.derived_origin_id.getReferredObject()]
event_name = get_event_filename(ev, "GCMT")
if output_folder:
event_name = os.path.join(output_folder, event_name)
cat.write(event_name, format="quakeml", validate=True)
print "Written file", event_name
def iris2quakeml(url, output_folder=None):
if "/spudservice/" not in url:
url = url.replace("/spud/", "/spudservice/")
if url.endswith("/"):
url += "quakeml"
else:
url += "/quakeml"
print(f"Downloading {url}...")
r = urllib.request.urlopen(url)
if r.code != 200:
r.close()
msg = "Error Downloading file!"
raise Exception(msg)
data = r.read()
r.close()
try:
cat = read_events(data)
except:
msg = "Could not read downloaded event data"
raise ValueError(msg)
cat.events = cat.events[:1]
ev = cat[0]
# Parse the event and get the preferred focal mechanism. Then get the
# origin and magnitude associated with that focal mechanism. All other
# focal mechanisms, origins and magnitudes will be removed. Just makes it
# simpler and less error prone.
if ev.preferred_focal_mechanism():
ev.focal_mechanisms = [ev.preferred_focal_mechanism()]
else:
ev.focal_mechanisms = [ev.focal_mechanisms[:1]]
# Set the origin and magnitudes of the event.
mt = ev.focal_mechanisms[0].moment_tensor
ev.magnitudes = [mt.moment_magnitude_id.get_referred_object()]
ev.origins = [mt.derived_origin_id.get_referred_object()]
event_filename = get_event_filename(ev, "GCMT")
if output_folder:
event_filename = os.path.join(output_folder, event_filename)
with pyasdf.ASDFDataSet(event_filename) as ds:
ds.add_quakeml(cat)
print("Written file", event_filename)
def add_new_events(comm,
count,
min_magnitude,
max_magnitude,
min_year=None,
max_year=None,
threshold_distance_in_km=50.0):
min_magnitude = float(min_magnitude)
max_magnitude = float(max_magnitude)
# Get the catalog.
cat = _read_GCMT_catalog(min_year=min_year, max_year=max_year)
# Filter with the magnitudes
cat = cat.filter("magnitude >= %.2f" % min_magnitude,
"magnitude <= %.2f" % max_magnitude)
# Filtering catalog to only contain events in the domain.
print("Filtering to only include events inside domain...")
# Coordinates and the Catalog will have the same order!
temp_cat = Catalog()
coordinates = []
for event in cat:
org = event.preferred_origin() or event.origins[0]
if not comm.query.point_in_domain(org.latitude, org.longitude):
continue
temp_cat.events.append(event)
coordinates.append((org.latitude, org.longitude))
cat = temp_cat
chosen_events = []
print("%i valid events remain. Starting selection process..." % len(cat))
existing_events = comm.events.get_all_events().values()
# Get the coordinates of all existing events.
existing_coordinates = [(_i["latitude"], _i["longitude"])
for _i in existing_events]
existing_origin_times = [_i["origin_time"] for _i in existing_events]
# Special case handling in case there are no preexisting events.
if not existing_coordinates:
idx = random.randint(0, len(cat) - 1)
chosen_events.append(cat[idx])
del cat.events[idx]
existing_coordinates.append(coordinates[idx])
del coordinates[idx]
_t = cat[idx].preferred_origin() or cat[idx].origins[0]
existing_origin_times.append(_t.time)
count -= 1
while count:
if not coordinates:
print("\tNo events left to select from. Stoping here.")
break
# Build kdtree and query for the point furthest away from any other
# point.
kdtree = SphericalNearestNeighbour(np.array(existing_coordinates))
distances = kdtree.query(np.array(coordinates), k=1)[0]
idx = np.argmax(distances)
event = cat[idx]
coods = coordinates[idx]
del cat.events[idx]
del coordinates[idx]
# Actual distance.
distance = EARTH_RADIUS * distances[idx]
if distance < threshold_distance_in_km:
print("\tNo events left with distance to the next closest event "
"of more then %.1f km. Stoping here." %
threshold_distance_in_km)
break
# Make sure it did not happen within one day of an existing event.
# This should also filter out duplicates.
_t = event.preferred_origin() or event.origins[0]
origin_time = _t.time
if min([abs(origin_time - _i) for _i in existing_origin_times]) < \
86400:
print("\tSelected event temporally to close to existing event. "
"Will not be chosen. Skipping to next event.")
continue
print("\tSelected event with the next closest event being %.1f km "
"away." % distance)
chosen_events.append(event)
existing_coordinates.append(coods)
count -= 1
print("Selected %i events." % len(chosen_events))
folder = comm.project.paths["events"]
for event in chosen_events:
filename = os.path.join(folder, get_event_filename(event, "GCMT"))
Catalog(events=[event]).write(filename,
format="quakeml",
validate=True)
print("Written %s" % (os.path.relpath(filename)))
def add_new_events(comm, count, min_magnitude, max_magnitude, min_year=None,
max_year=None, threshold_distance_in_km=50.0):
min_magnitude = float(min_magnitude)
max_magnitude = float(max_magnitude)
# Get the catalog.
cat = _read_GCMT_catalog(min_year=min_year, max_year=max_year)
# Filter with the magnitudes
cat = cat.filter("magnitude >= %.2f" % min_magnitude,
"magnitude <= %.2f" % max_magnitude)
# Filtering catalog to only contain events in the domain.
print("Filtering to only include events inside domain...")
# Coordinates and the Catalog will have the same order!
temp_cat = Catalog()
coordinates = []
for event in cat:
org = event.preferred_origin() or event.origins[0]
if not comm.query.point_in_domain(org.latitude, org.longitude):
continue
temp_cat.events.append(event)
coordinates.append((org.latitude, org.longitude))
cat = temp_cat
chosen_events = []
print("%i valid events remain. Starting selection process..." % len(cat))
existing_events = comm.events.get_all_events().values()
# Get the coordinates of all existing events.
existing_coordinates = [
(_i["latitude"], _i["longitude"]) for _i in existing_events]
existing_origin_times = [_i["origin_time"] for _i in existing_events]
# Special case handling in case there are no preexisting events.
if not existing_coordinates:
idx = random.randint(0, len(cat) - 1)
chosen_events.append(cat[idx])
del cat.events[idx]
existing_coordinates.append(coordinates[idx])
del coordinates[idx]
_t = cat[idx].preferred_origin() or cat[idx].origins[0]
existing_origin_times.append(_t.time)
count -= 1
while count:
if not coordinates:
print("\tNo events left to select from. Stoping here.")
break
# Build kdtree and query for the point furthest away from any other
# point.
kdtree = SphericalNearestNeighbour(np.array(existing_coordinates))
distances = kdtree.query(np.array(coordinates), k=1)[0]
idx = np.argmax(distances)
event = cat[idx]
coods = coordinates[idx]
del cat.events[idx]
del coordinates[idx]
# Actual distance.
distance = EARTH_RADIUS * distances[idx]
if distance < threshold_distance_in_km:
print("\tNo events left with distance to the next closest event "
"of more then %.1f km. Stoping here." %
threshold_distance_in_km)
break
# Make sure it did not happen within one day of an existing event.
# This should also filter out duplicates.
_t = event.preferred_origin() or event.origins[0]
origin_time = _t.time
if min([abs(origin_time - _i) for _i in existing_origin_times]) < \
86400:
print("\tSelected event temporally to close to existing event. "
"Will not be chosen. Skipping to next event.")
continue
print("\tSelected event with the next closest event being %.1f km "
"away." % distance)
chosen_events.append(event)
existing_coordinates.append(coods)
count -= 1
print("Selected %i events." % len(chosen_events))
folder = comm.project.paths["events"]
for event in chosen_events:
filename = os.path.join(folder, get_event_filename(event, "GCMT"))
Catalog(events=[event]).write(filename, format="quakeml",
validate=True)
print("Written %s" % (os.path.relpath(filename)))
